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Sumo Logic Delivers 3-Step Onboarding for Kubernetes Observability

Sumo Logic unveiled a new process to deliver Kubernetes observability in just a few clicks. This simplified process streamlines the Sumo Logic collection process and ensures faster time-to-value for Kubernetes observability.

This new experience makes it easy for developers to get up and running quickly with Kubernetes observability by:

- Establishing appropriate collection for the Kubernetes environment (Orchestration, Infrastructure & App Data) with the proper metadata.

- Installing the relevant app dashboards to view data and help diagnose and troubleshoot issues.

- Validating automatically generated alerts.

“Developers are at the heart of challenging the status quo and getting the digital experiences we crave into service. Digital experiences simply do not advance without the needed visibility for developers to make them a reality,” said Christian Beedgen, CTO and Co-Founder, Sumo Logic. “Today, we take another step in delivering on the promise to deliver a premium developer experience. Onboarding Kubernetes data into Sumo Logic has never been faster, smarter, or more secure.”

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Sumo Logic Delivers 3-Step Onboarding for Kubernetes Observability

Sumo Logic unveiled a new process to deliver Kubernetes observability in just a few clicks. This simplified process streamlines the Sumo Logic collection process and ensures faster time-to-value for Kubernetes observability.

This new experience makes it easy for developers to get up and running quickly with Kubernetes observability by:

- Establishing appropriate collection for the Kubernetes environment (Orchestration, Infrastructure & App Data) with the proper metadata.

- Installing the relevant app dashboards to view data and help diagnose and troubleshoot issues.

- Validating automatically generated alerts.

“Developers are at the heart of challenging the status quo and getting the digital experiences we crave into service. Digital experiences simply do not advance without the needed visibility for developers to make them a reality,” said Christian Beedgen, CTO and Co-Founder, Sumo Logic. “Today, we take another step in delivering on the promise to deliver a premium developer experience. Onboarding Kubernetes data into Sumo Logic has never been faster, smarter, or more secure.”

The Latest

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

Government agencies are largely misjudging their level of AI governance as the technology permeates their organization, according to Racing to Deploy: How Public Sector AI Adoption is Moving Faster Than the Foundations Needed to Support It, a new report from SolarWinds ...